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Reinforcement Learning Research Engineer – Exploration & Decision Intelligence (m/w/d)

Autonomous Teaming

📍Munich (DEU)

unknownEngineering & Tech

Posted 1mo ago · via personio

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Job Description

What we offer

  • Opportunity to work on a new solution from scratch in a technical complex environment
  • Work in an international, agile, cross-functional team creating the future of autonomous systems
  • Grow your career in a expanding and ambitious engineering team
  • Build innovative products using state-of-the-art technologies in AI, robotics, and autonomy 
  • Benefit from a steep learning curve and continuous development
  • Enjoy team events and a strong, collaborative culture

Your mission

Build real autonomous systems that operate in the real world, not in the lab. 

Join our engineering team of a new product and help build the core autonomy that powers our next generation robotic systems used for defense and mission-critical operations. You will design, implement, and harden robotic software that must perform under real operational conditions - outdoors, under uncertainty, with real consequences. Your work will directly shape the reliability, safety, and tactical capability of the systems we deliver. 
 
  • Research and prototype novel RL algorithms (e.g. exploration, POMDPs, multi-agent systems) 
  • Define, design and implement use-cases for DRL on edge devices 
  • Translate theory into scalable systems with support from our engineering teams 
  • Collaborate with simulation, autonomy and AI infrastructure teams 
  • Develop decision-making for intelligent behavior and architectures 

Your profile

  • Deep knowledge of RL theory and practice: policy gradients, value iteration, Q-learning, etc. 
  • Experience with ML training in physics based simulation (Gazebo, IsaacSim, Mujoco, Carla, etc.).
  • Strong Programming proficiency (Python, C/C++).
  • Comfortable with ML tooling and maintaining ML pipelines (Pytorch Lightning, MlFlow, etc.).
  • Have experience with deploying ML methods to physical devices.
  • Experience with version control (git).
  • Familiarity with statistics, evaluation methods and experiment design.
  • You think rigorously and build practically.

Nice to have

  • PhD in Reinforcement Learning, Robot Engineering or equivalent with experience in deploying developed methods to real robots.
  • OR masters degree in relevant field with extensive experience in RL.
  • Experience with sensor based end-to-end ML architectures.
  • Familiar with Transformers, Attention, Graphs, VLAs and other modern day ML building blocks.
  • Publications at NeurIPS, ICLR, ICML, ICRA, IROS, etc. are a plus 
  • Experience with robotics middleware (ISAAC, ROS/ROS2, etc.)

Why us?

  • Willingness to travel
  • Citizenship of NATO member country or closed allied are mandatory

Details

Department
Engineering & Tech
Work Type
unknown
Locations
Munich (DEU)
Posted
April 8, 2026
Source
personio